Salience Bias

Details:

The tendency to focus on items that are more prominent or emotionally striking and ignore those that are unremarkable, even though this difference is often irrelevant by objective standards.

References:

Structural Analysis:

(Results of dataset analysis for patterns in structure, placement, tone, context, coreference, correlatives, and so on will go here.)

Proposed Algorithms:

(Proposed combinations of factors from the above analyses in algorithmic form for automated detection will go here.)

Positive Detection:

(Algorithms for bias-positive detection will go here.)

False-positive Detection:

(Algorithms for false-positive detection/filtering of the above bias-positive algorithms will go here)

Certainty Mapping:

(Algorithms for the probability mapping between N mathematical dimensions for positive and false-positive algorithms will go here)

Successful Algorithms:

(Tested successful algorithms will go here, along with their respective accuracy metrics and error data for further refinement.)